On 3/10/13, QT <rdirective@gmail.com> wrote:
> Dear all,
>> I'm at my wits end. I've followed Intel's own
> instructions<http://software.intel.com/en-us/articles/numpyscipy-with-intel-mkl>on
> how to compile Numpy with Intel MKL. Everything compiled and linked
> fine and I've installed it locally in my user folder...There is one nasty
> problem. When one calls the numpy library to do some computation, it does
> not use all of the available threads. I have 8 "cores" on my machine and
> it only uses 4 of them. The MKL_NUM_THREADS environmental variable can be
> set to tune the number of threads but setting it to 8 does not change
> anything. Indeed, setting it to 3 does limit the threads to 3....What is
> going on?
Does your computer have 8 physical cores, or 4 cores that look like 8
because of hyperthreading?
Warren
>> As a comparison, the numpy (version 1.4.1, installed from yum, which uses
> BLAS+ATLAS) uses all 8 threads. I do not get this.
>> You can run this test program
>> python -mtimeit -s'import numpy as np; a = np.random.randn(1e3,1e3)'
> 'np.dot(a, a)'
>> There is one saving grace, the local numpy built with MKL is much faster
> than the system's numpy.
>> I hope someone can help me. Searching the internet has been fruitless.
>> Best,
> Quyen
>> My site.cfg for numpy (1.7.0)
> [mkl]
> library_dirs = /opt/intel/mkl/lib/intel64
> include_dirs = /opt/intel/mkl/include
> mkl_libs = mkl_rt
> lapack_libs =
>> I've edited line 37 of numpy/distutils/intelcompiler.py
> self.cc_exe = 'icc -O3 -fPIC -fp-model strict -fomit-frame-pointer -openmp
> -parallel -DMKL_ILP64'
>> Also line 54 of numpy/distutils/fcompiler/intel.py
> return ['-i8 -xhost -openmp -fp-model strict']
>> My .bash_profile also contains the lines:
> source /opt/intel/bin/compilervars.sh intel64
> source /opt/intel/mkl/bin/mklvars.sh intel64
>> The above is needed to set the LD_LIBRARY_PATH so that Python can source
> the intel dynamic library when numpy is called.
>